R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1579
+ ,0
+ ,4.0
+ ,45.7
+ ,2146
+ ,0
+ ,5.9
+ ,81.9
+ ,2462
+ ,0
+ ,7.1
+ ,56.8
+ ,3695
+ ,0
+ ,10.5
+ ,65.1
+ ,4831
+ ,0
+ ,15.1
+ ,86.2
+ ,5134
+ ,0
+ ,16.8
+ ,35.1
+ ,6250
+ ,0
+ ,15.3
+ ,133.8
+ ,5760
+ ,0
+ ,18.4
+ ,34.5
+ ,6249
+ ,0
+ ,16.1
+ ,69.9
+ ,2917
+ ,0
+ ,11.3
+ ,98.3
+ ,1741
+ ,0
+ ,7.9
+ ,86.7
+ ,2359
+ ,0
+ ,5.6
+ ,58.2
+ ,1511
+ ,1
+ ,3.4
+ ,83.6
+ ,2059
+ ,0
+ ,4.8
+ ,83.5
+ ,2635
+ ,0
+ ,6.5
+ ,112.3
+ ,2867
+ ,0
+ ,8.5
+ ,134.3
+ ,4403
+ ,0
+ ,15.1
+ ,30.0
+ ,5720
+ ,0
+ ,15.7
+ ,44.5
+ ,4502
+ ,0
+ ,18.7
+ ,120.1
+ ,5749
+ ,0
+ ,19.2
+ ,43.4
+ ,5627
+ ,0
+ ,12.9
+ ,199.4
+ ,2846
+ ,0
+ ,14.4
+ ,68.1
+ ,1762
+ ,0
+ ,6.2
+ ,99.8
+ ,2429
+ ,0
+ ,3.3
+ ,69.5
+ ,1169
+ ,0
+ ,4.6
+ ,71.3
+ ,2154
+ ,1
+ ,7.2
+ ,167.8
+ ,2249
+ ,0
+ ,7.8
+ ,66.3
+ ,2687
+ ,0
+ ,9.9
+ ,41.9
+ ,4359
+ ,0
+ ,13.6
+ ,57.2
+ ,5382
+ ,0
+ ,17.1
+ ,72.3
+ ,4459
+ ,0
+ ,17.8
+ ,96.5
+ ,6398
+ ,0
+ ,18.6
+ ,172.1
+ ,4596
+ ,0
+ ,14.7
+ ,25.8
+ ,3024
+ ,0
+ ,10.5
+ ,105.1
+ ,1887
+ ,0
+ ,8.6
+ ,92.2
+ ,2070
+ ,0
+ ,4.4
+ ,109.3
+ ,1351
+ ,0
+ ,2.3
+ ,101.7
+ ,2218
+ ,0
+ ,2.8
+ ,29.1
+ ,2461
+ ,1
+ ,8.8
+ ,34.6
+ ,3028
+ ,0
+ ,10.7
+ ,46.7
+ ,4784
+ ,0
+ ,13.9
+ ,82.0
+ ,4975
+ ,0
+ ,19.3
+ ,34.4
+ ,4607
+ ,0
+ ,19.5
+ ,72.7
+ ,6249
+ ,0
+ ,20.4
+ ,44.4
+ ,4809
+ ,0
+ ,15.3
+ ,31.0
+ ,3157
+ ,0
+ ,7.9
+ ,64.0
+ ,1910
+ ,0
+ ,8.3
+ ,65.4
+ ,2228
+ ,0
+ ,4.5
+ ,64.5
+ ,1594
+ ,0
+ ,3.2
+ ,153.8
+ ,2467
+ ,0
+ ,5.0
+ ,48.8
+ ,2222
+ ,0
+ ,6.6
+ ,25.0
+ ,3607
+ ,1
+ ,11.1
+ ,37.2
+ ,4685
+ ,0
+ ,12.8
+ ,40.8
+ ,4962
+ ,0
+ ,16.3
+ ,78.4
+ ,5770
+ ,0
+ ,17.4
+ ,112.4
+ ,5480
+ ,0
+ ,18.9
+ ,122.7
+ ,5000
+ ,0
+ ,15.8
+ ,82.9
+ ,3228
+ ,0
+ ,11.7
+ ,67.6
+ ,1993
+ ,0
+ ,6.4
+ ,78.4
+ ,2288
+ ,0
+ ,2.9
+ ,65.7
+ ,1580
+ ,0
+ ,4.7
+ ,44.9
+ ,2111
+ ,0
+ ,2.4
+ ,80.9
+ ,2192
+ ,0
+ ,7.2
+ ,38.8
+ ,3601
+ ,0
+ ,10.7
+ ,46.1
+ ,4665
+ ,1
+ ,13.4
+ ,60.0
+ ,4876
+ ,0
+ ,18.5
+ ,53.9
+ ,5813
+ ,0
+ ,18.3
+ ,123.5
+ ,5589
+ ,0
+ ,16.8
+ ,69.5
+ ,5331
+ ,0
+ ,16.6
+ ,74.2
+ ,3075
+ ,0
+ ,14.1
+ ,47.0
+ ,2002
+ ,0
+ ,6.1
+ ,60.9
+ ,2306
+ ,0
+ ,3.5
+ ,51.4
+ ,1507
+ ,0
+ ,1.7
+ ,18.7
+ ,1992
+ ,0
+ ,2.3
+ ,88.1
+ ,2487
+ ,0
+ ,4.5
+ ,65.3
+ ,3490
+ ,0
+ ,9.3
+ ,46.0
+ ,4647
+ ,0
+ ,14.2
+ ,115.6
+ ,5594
+ ,1
+ ,17.3
+ ,25.8
+ ,5611
+ ,0
+ ,23.0
+ ,48.1
+ ,5788
+ ,0
+ ,16.3
+ ,202.3
+ ,6204
+ ,0
+ ,18.4
+ ,9.2
+ ,3013
+ ,0
+ ,14.2
+ ,56.3
+ ,1931
+ ,0
+ ,9.1
+ ,71.6
+ ,2549
+ ,0
+ ,5.9
+ ,93.0
+ ,1504
+ ,0
+ ,7.2
+ ,82.3
+ ,2090
+ ,0
+ ,6.8
+ ,95.4
+ ,2702
+ ,0
+ ,8.0
+ ,61.9
+ ,2939
+ ,0
+ ,14.3
+ ,0.0
+ ,4500
+ ,0
+ ,14.6
+ ,103.4
+ ,6208
+ ,0
+ ,17.5
+ ,99.2
+ ,6415
+ ,1
+ ,17.2
+ ,96.7
+ ,5657
+ ,0
+ ,17.2
+ ,56.9
+ ,5964
+ ,0
+ ,14.1
+ ,57.6
+ ,3163
+ ,0
+ ,10.5
+ ,65.2
+ ,1997
+ ,0
+ ,6.8
+ ,71.7
+ ,2422
+ ,0
+ ,4.1
+ ,89.2
+ ,1376
+ ,0
+ ,6.5
+ ,70.7
+ ,2202
+ ,0
+ ,6.1
+ ,35.4
+ ,2683
+ ,0
+ ,6.3
+ ,140.5
+ ,3303
+ ,0
+ ,9.3
+ ,45.4
+ ,5202
+ ,0
+ ,16.4
+ ,53.9
+ ,5231
+ ,0
+ ,16.1
+ ,69.9
+ ,4880
+ ,0
+ ,18.0
+ ,101.9
+ ,7998
+ ,1
+ ,17.6
+ ,89.3
+ ,4977
+ ,0
+ ,14.0
+ ,70.7
+ ,3531
+ ,0
+ ,10.5
+ ,72.4
+ ,2025
+ ,0
+ ,6.9
+ ,67.6
+ ,2205
+ ,0
+ ,2.8
+ ,43.3
+ ,1442
+ ,0
+ ,0.7
+ ,62.9
+ ,2238
+ ,0
+ ,3.6
+ ,57.1
+ ,2179
+ ,0
+ ,6.7
+ ,68.2
+ ,3218
+ ,0
+ ,12.5
+ ,47.1
+ ,5139
+ ,0
+ ,14.4
+ ,43.1
+ ,4990
+ ,0
+ ,16.5
+ ,64.5
+ ,4914
+ ,0
+ ,18.7
+ ,73.1
+ ,6084
+ ,0
+ ,19.4
+ ,37.7
+ ,5672
+ ,1
+ ,15.8
+ ,29.1
+ ,3548
+ ,0
+ ,11.3
+ ,105.0
+ ,1793
+ ,0
+ ,9.7
+ ,98.0
+ ,2086
+ ,0
+ ,2.9
+ ,80.8)
+ ,dim=c(4
+ ,120)
+ ,dimnames=list(c('Huwelijken'
+ ,'Specialedag'
+ ,'Temperatuur'
+ ,'Neerslag')
+ ,1:120))
> y <- array(NA,dim=c(4,120),dimnames=list(c('Huwelijken','Specialedag','Temperatuur','Neerslag'),1:120))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Huwelijken Specialedag Temperatuur Neerslag
1 1579 0 4.0 45.7
2 2146 0 5.9 81.9
3 2462 0 7.1 56.8
4 3695 0 10.5 65.1
5 4831 0 15.1 86.2
6 5134 0 16.8 35.1
7 6250 0 15.3 133.8
8 5760 0 18.4 34.5
9 6249 0 16.1 69.9
10 2917 0 11.3 98.3
11 1741 0 7.9 86.7
12 2359 0 5.6 58.2
13 1511 1 3.4 83.6
14 2059 0 4.8 83.5
15 2635 0 6.5 112.3
16 2867 0 8.5 134.3
17 4403 0 15.1 30.0
18 5720 0 15.7 44.5
19 4502 0 18.7 120.1
20 5749 0 19.2 43.4
21 5627 0 12.9 199.4
22 2846 0 14.4 68.1
23 1762 0 6.2 99.8
24 2429 0 3.3 69.5
25 1169 0 4.6 71.3
26 2154 1 7.2 167.8
27 2249 0 7.8 66.3
28 2687 0 9.9 41.9
29 4359 0 13.6 57.2
30 5382 0 17.1 72.3
31 4459 0 17.8 96.5
32 6398 0 18.6 172.1
33 4596 0 14.7 25.8
34 3024 0 10.5 105.1
35 1887 0 8.6 92.2
36 2070 0 4.4 109.3
37 1351 0 2.3 101.7
38 2218 0 2.8 29.1
39 2461 1 8.8 34.6
40 3028 0 10.7 46.7
41 4784 0 13.9 82.0
42 4975 0 19.3 34.4
43 4607 0 19.5 72.7
44 6249 0 20.4 44.4
45 4809 0 15.3 31.0
46 3157 0 7.9 64.0
47 1910 0 8.3 65.4
48 2228 0 4.5 64.5
49 1594 0 3.2 153.8
50 2467 0 5.0 48.8
51 2222 0 6.6 25.0
52 3607 1 11.1 37.2
53 4685 0 12.8 40.8
54 4962 0 16.3 78.4
55 5770 0 17.4 112.4
56 5480 0 18.9 122.7
57 5000 0 15.8 82.9
58 3228 0 11.7 67.6
59 1993 0 6.4 78.4
60 2288 0 2.9 65.7
61 1580 0 4.7 44.9
62 2111 0 2.4 80.9
63 2192 0 7.2 38.8
64 3601 0 10.7 46.1
65 4665 1 13.4 60.0
66 4876 0 18.5 53.9
67 5813 0 18.3 123.5
68 5589 0 16.8 69.5
69 5331 0 16.6 74.2
70 3075 0 14.1 47.0
71 2002 0 6.1 60.9
72 2306 0 3.5 51.4
73 1507 0 1.7 18.7
74 1992 0 2.3 88.1
75 2487 0 4.5 65.3
76 3490 0 9.3 46.0
77 4647 0 14.2 115.6
78 5594 1 17.3 25.8
79 5611 0 23.0 48.1
80 5788 0 16.3 202.3
81 6204 0 18.4 9.2
82 3013 0 14.2 56.3
83 1931 0 9.1 71.6
84 2549 0 5.9 93.0
85 1504 0 7.2 82.3
86 2090 0 6.8 95.4
87 2702 0 8.0 61.9
88 2939 0 14.3 0.0
89 4500 0 14.6 103.4
90 6208 0 17.5 99.2
91 6415 1 17.2 96.7
92 5657 0 17.2 56.9
93 5964 0 14.1 57.6
94 3163 0 10.5 65.2
95 1997 0 6.8 71.7
96 2422 0 4.1 89.2
97 1376 0 6.5 70.7
98 2202 0 6.1 35.4
99 2683 0 6.3 140.5
100 3303 0 9.3 45.4
101 5202 0 16.4 53.9
102 5231 0 16.1 69.9
103 4880 0 18.0 101.9
104 7998 1 17.6 89.3
105 4977 0 14.0 70.7
106 3531 0 10.5 72.4
107 2025 0 6.9 67.6
108 2205 0 2.8 43.3
109 1442 0 0.7 62.9
110 2238 0 3.6 57.1
111 2179 0 6.7 68.2
112 3218 0 12.5 47.1
113 5139 0 14.4 43.1
114 4990 0 16.5 64.5
115 4914 0 18.7 73.1
116 6084 0 19.4 37.7
117 5672 1 15.8 29.1
118 3548 0 11.3 105.0
119 1793 0 9.7 98.0
120 2086 0 2.9 80.8
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Specialedag Temperatuur Neerslag
505.099 525.423 259.288 2.906
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1590.77 -473.34 99.66 462.25 2144.46
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 505.099 196.234 2.574 0.0113 *
Specialedag 525.423 245.616 2.139 0.0345 *
Temperatuur 259.288 11.644 22.269 <2e-16 ***
Neerslag 2.906 1.825 1.593 0.1139
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 706.8 on 116 degrees of freedom
Multiple R-squared: 0.8152, Adjusted R-squared: 0.8104
F-statistic: 170.5 on 3 and 116 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.14822243 0.2964449 0.8517776
[2,] 0.06765399 0.1353080 0.9323460
[3,] 0.16525154 0.3305031 0.8347485
[4,] 0.50759684 0.9848063 0.4924032
[5,] 0.62785022 0.7442996 0.3721498
[6,] 0.58389969 0.8322006 0.4161003
[7,] 0.48852801 0.9770560 0.5114720
[8,] 0.40692746 0.8138549 0.5930725
[9,] 0.31854990 0.6370998 0.6814501
[10,] 0.26314084 0.5262817 0.7368592
[11,] 0.21753099 0.4350620 0.7824690
[12,] 0.22141393 0.4428279 0.7785861
[13,] 0.55407965 0.8918407 0.4459203
[14,] 0.48636804 0.9727361 0.5136320
[15,] 0.58413836 0.8317233 0.4158616
[16,] 0.84224327 0.3155135 0.1577567
[17,] 0.82478696 0.3504261 0.1752130
[18,] 0.85646825 0.2870635 0.1435317
[19,] 0.84794364 0.3041127 0.1520564
[20,] 0.86405138 0.2718972 0.1359486
[21,] 0.83922786 0.3215443 0.1607721
[22,] 0.81327634 0.3734473 0.1867237
[23,] 0.76957086 0.4608583 0.2304291
[24,] 0.72186508 0.5562698 0.2781349
[25,] 0.77465713 0.4506857 0.2253429
[26,] 0.74255927 0.5148815 0.2574407
[27,] 0.69738235 0.6052353 0.3026176
[28,] 0.67201024 0.6559795 0.3279898
[29,] 0.73776476 0.5244705 0.2622352
[30,] 0.69297283 0.6140543 0.3070272
[31,] 0.64303213 0.7139357 0.3569679
[32,] 0.69847285 0.6030543 0.3015271
[33,] 0.71183200 0.5763360 0.2881680
[34,] 0.67460003 0.6507999 0.3254000
[35,] 0.64243350 0.7151330 0.3575665
[36,] 0.62882679 0.7423464 0.3711732
[37,] 0.70848105 0.5830379 0.2915190
[38,] 0.67639330 0.6472134 0.3236067
[39,] 0.63574565 0.7285087 0.3642543
[40,] 0.60320386 0.7935923 0.3967961
[41,] 0.64293547 0.7141291 0.3570645
[42,] 0.60611058 0.7877788 0.3938894
[43,] 0.56341525 0.8731695 0.4365847
[44,] 0.54056802 0.9188640 0.4594320
[45,] 0.48637318 0.9727464 0.5136268
[46,] 0.49338509 0.9867702 0.5066149
[47,] 0.50848253 0.9830349 0.4915175
[48,] 0.45467810 0.9093562 0.5453219
[49,] 0.42353638 0.8470728 0.5764636
[50,] 0.37893378 0.7578676 0.6210662
[51,] 0.33229937 0.6645987 0.6677006
[52,] 0.30925648 0.6185130 0.6907435
[53,] 0.28151706 0.5630341 0.7184829
[54,] 0.29686408 0.5937282 0.7031359
[55,] 0.26060631 0.5212126 0.7393937
[56,] 0.25913442 0.5182688 0.7408656
[57,] 0.22529496 0.4505899 0.7747050
[58,] 0.19002291 0.3800458 0.8099771
[59,] 0.19675933 0.3935187 0.8032407
[60,] 0.18060405 0.3612081 0.8193960
[61,] 0.15079747 0.3015949 0.8492025
[62,] 0.14131032 0.2826206 0.8586897
[63,] 0.12031921 0.2406384 0.8796808
[64,] 0.17974200 0.3594840 0.8202580
[65,] 0.15244565 0.3048913 0.8475543
[66,] 0.15156273 0.3031255 0.8484373
[67,] 0.13404003 0.2680801 0.8659600
[68,] 0.12361329 0.2472266 0.8763867
[69,] 0.11590282 0.2318056 0.8840972
[70,] 0.10140402 0.2028080 0.8985960
[71,] 0.07952023 0.1590405 0.9204798
[72,] 0.08520801 0.1704160 0.9147920
[73,] 0.10537714 0.2107543 0.8946229
[74,] 0.09378190 0.1875638 0.9062181
[75,] 0.11165752 0.2233150 0.8883425
[76,] 0.19473269 0.3894654 0.8052673
[77,] 0.26809361 0.5361872 0.7319064
[78,] 0.22705125 0.4541025 0.7729487
[79,] 0.30370820 0.6074164 0.6962918
[80,] 0.27918558 0.5583712 0.7208144
[81,] 0.23182526 0.4636505 0.7681747
[82,] 0.39370435 0.7874087 0.6062957
[83,] 0.33574175 0.6714835 0.6642583
[84,] 0.38555894 0.7711179 0.6144411
[85,] 0.37468746 0.7493749 0.6253125
[86,] 0.34273295 0.6854659 0.6572671
[87,] 0.63114543 0.7377091 0.3688546
[88,] 0.57551109 0.8489778 0.4244889
[89,] 0.55076918 0.8984616 0.4492308
[90,] 0.52485296 0.9502941 0.4751470
[91,] 0.64024746 0.7195051 0.3597525
[92,] 0.58309069 0.8338186 0.4169093
[93,] 0.53246408 0.9350718 0.4675359
[94,] 0.45773626 0.9154725 0.5422637
[95,] 0.39248101 0.7849620 0.6075190
[96,] 0.34929055 0.6985811 0.6507094
[97,] 0.28661325 0.5732265 0.7133868
[98,] 0.77306847 0.4538631 0.2269315
[99,] 0.81934612 0.3613078 0.1806539
[100,] 0.75783277 0.4843345 0.2421672
[101,] 0.73823509 0.5235298 0.2617649
[102,] 0.65257860 0.6948428 0.3474214
[103,] 0.54769885 0.9046023 0.4523012
[104,] 0.44196004 0.8839201 0.5580400
[105,] 0.34792661 0.6958532 0.6520734
[106,] 0.57692889 0.8461422 0.4230711
[107,] 0.41506029 0.8301206 0.5849397
> postscript(file="/var/www/html/rcomp/tmp/1eild1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/26r2g1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/36r2g1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/46r2g1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5hiji1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 120
Frequency = 1
1 2 3 4 5 6
-96.072801 -126.930269 -49.127419 278.169159 160.118461 170.841800
7 8 9 10 11 12
1388.919184 383.724031 1366.203253 -803.751973 -1064.457643 232.736433
13 14 15 16 17 18
-644.073134 66.636923 118.144036 -232.372313 -104.545470 1014.739573
19 20 21 22 23 24
-1200.844853 139.426858 1197.555914 -1590.774925 -640.740223 866.258345
25 26 27 28 29 30
-736.048084 -1231.082832 -471.239545 -506.830764 161.334919 232.939566
31 32 33 34 35 36
-941.895696 569.954537 204.376532 -509.084271 -1115.944426 106.368854
37 38 39 40 41 42
-46.037184 902.318550 -951.820481 -387.211960 436.471249 -634.344968
43 44 45 46 47 48
-1165.515323 325.374345 246.690498 417.516179 -937.268084 368.643847
49 50 51 52 53 54
-187.816909 523.629077 -67.061702 -409.740460 742.429610 2.641703
55 56 57 58 59 60
426.608958 -282.259022 157.207432 -507.242858 -399.402334 840.017814
61 62 63 64 65 66
-274.249669 748.485751 -292.742224 187.531841 -14.368422 -582.587730
67 68 69 70 71 72
203.988998 525.863850 306.061768 -1222.664697 -261.754914 744.005326
73 74 75 76 77 78
506.761771 634.488982 625.318778 439.826349 124.031823 2.803184
79 80 81 82 83 84
-997.529148 468.546704 901.254325 -1337.622467 -1141.718150 243.809405
85 86 87 88 89 90
-1107.167828 -455.525434 -57.309364 -1273.924613 -91.226273 877.043742
91 92 93 94 95 96
643.672828 526.768288 1635.528144 -254.121475 -479.645277 594.572746
97 98 99 100 101 102
-1019.952397 12.356647 136.043064 254.570150 287.918080 348.203253
103 104 105 106 107 108
-588.447605 2144.464320 636.383994 92.952908 -465.658149 848.048582
109 110 111 112 113 114
572.590212 633.510364 -261.544254 -665.093760 774.883468 19.182073
115 116 117 118 119 120
-652.247073 439.135276 460.144998 -192.224423 -1512.018502 594.132144
> postscript(file="/var/www/html/rcomp/tmp/6hiji1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 -96.072801 NA
1 -126.930269 -96.072801
2 -49.127419 -126.930269
3 278.169159 -49.127419
4 160.118461 278.169159
5 170.841800 160.118461
6 1388.919184 170.841800
7 383.724031 1388.919184
8 1366.203253 383.724031
9 -803.751973 1366.203253
10 -1064.457643 -803.751973
11 232.736433 -1064.457643
12 -644.073134 232.736433
13 66.636923 -644.073134
14 118.144036 66.636923
15 -232.372313 118.144036
16 -104.545470 -232.372313
17 1014.739573 -104.545470
18 -1200.844853 1014.739573
19 139.426858 -1200.844853
20 1197.555914 139.426858
21 -1590.774925 1197.555914
22 -640.740223 -1590.774925
23 866.258345 -640.740223
24 -736.048084 866.258345
25 -1231.082832 -736.048084
26 -471.239545 -1231.082832
27 -506.830764 -471.239545
28 161.334919 -506.830764
29 232.939566 161.334919
30 -941.895696 232.939566
31 569.954537 -941.895696
32 204.376532 569.954537
33 -509.084271 204.376532
34 -1115.944426 -509.084271
35 106.368854 -1115.944426
36 -46.037184 106.368854
37 902.318550 -46.037184
38 -951.820481 902.318550
39 -387.211960 -951.820481
40 436.471249 -387.211960
41 -634.344968 436.471249
42 -1165.515323 -634.344968
43 325.374345 -1165.515323
44 246.690498 325.374345
45 417.516179 246.690498
46 -937.268084 417.516179
47 368.643847 -937.268084
48 -187.816909 368.643847
49 523.629077 -187.816909
50 -67.061702 523.629077
51 -409.740460 -67.061702
52 742.429610 -409.740460
53 2.641703 742.429610
54 426.608958 2.641703
55 -282.259022 426.608958
56 157.207432 -282.259022
57 -507.242858 157.207432
58 -399.402334 -507.242858
59 840.017814 -399.402334
60 -274.249669 840.017814
61 748.485751 -274.249669
62 -292.742224 748.485751
63 187.531841 -292.742224
64 -14.368422 187.531841
65 -582.587730 -14.368422
66 203.988998 -582.587730
67 525.863850 203.988998
68 306.061768 525.863850
69 -1222.664697 306.061768
70 -261.754914 -1222.664697
71 744.005326 -261.754914
72 506.761771 744.005326
73 634.488982 506.761771
74 625.318778 634.488982
75 439.826349 625.318778
76 124.031823 439.826349
77 2.803184 124.031823
78 -997.529148 2.803184
79 468.546704 -997.529148
80 901.254325 468.546704
81 -1337.622467 901.254325
82 -1141.718150 -1337.622467
83 243.809405 -1141.718150
84 -1107.167828 243.809405
85 -455.525434 -1107.167828
86 -57.309364 -455.525434
87 -1273.924613 -57.309364
88 -91.226273 -1273.924613
89 877.043742 -91.226273
90 643.672828 877.043742
91 526.768288 643.672828
92 1635.528144 526.768288
93 -254.121475 1635.528144
94 -479.645277 -254.121475
95 594.572746 -479.645277
96 -1019.952397 594.572746
97 12.356647 -1019.952397
98 136.043064 12.356647
99 254.570150 136.043064
100 287.918080 254.570150
101 348.203253 287.918080
102 -588.447605 348.203253
103 2144.464320 -588.447605
104 636.383994 2144.464320
105 92.952908 636.383994
106 -465.658149 92.952908
107 848.048582 -465.658149
108 572.590212 848.048582
109 633.510364 572.590212
110 -261.544254 633.510364
111 -665.093760 -261.544254
112 774.883468 -665.093760
113 19.182073 774.883468
114 -652.247073 19.182073
115 439.135276 -652.247073
116 460.144998 439.135276
117 -192.224423 460.144998
118 -1512.018502 -192.224423
119 594.132144 -1512.018502
120 NA 594.132144
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -126.930269 -96.072801
[2,] -49.127419 -126.930269
[3,] 278.169159 -49.127419
[4,] 160.118461 278.169159
[5,] 170.841800 160.118461
[6,] 1388.919184 170.841800
[7,] 383.724031 1388.919184
[8,] 1366.203253 383.724031
[9,] -803.751973 1366.203253
[10,] -1064.457643 -803.751973
[11,] 232.736433 -1064.457643
[12,] -644.073134 232.736433
[13,] 66.636923 -644.073134
[14,] 118.144036 66.636923
[15,] -232.372313 118.144036
[16,] -104.545470 -232.372313
[17,] 1014.739573 -104.545470
[18,] -1200.844853 1014.739573
[19,] 139.426858 -1200.844853
[20,] 1197.555914 139.426858
[21,] -1590.774925 1197.555914
[22,] -640.740223 -1590.774925
[23,] 866.258345 -640.740223
[24,] -736.048084 866.258345
[25,] -1231.082832 -736.048084
[26,] -471.239545 -1231.082832
[27,] -506.830764 -471.239545
[28,] 161.334919 -506.830764
[29,] 232.939566 161.334919
[30,] -941.895696 232.939566
[31,] 569.954537 -941.895696
[32,] 204.376532 569.954537
[33,] -509.084271 204.376532
[34,] -1115.944426 -509.084271
[35,] 106.368854 -1115.944426
[36,] -46.037184 106.368854
[37,] 902.318550 -46.037184
[38,] -951.820481 902.318550
[39,] -387.211960 -951.820481
[40,] 436.471249 -387.211960
[41,] -634.344968 436.471249
[42,] -1165.515323 -634.344968
[43,] 325.374345 -1165.515323
[44,] 246.690498 325.374345
[45,] 417.516179 246.690498
[46,] -937.268084 417.516179
[47,] 368.643847 -937.268084
[48,] -187.816909 368.643847
[49,] 523.629077 -187.816909
[50,] -67.061702 523.629077
[51,] -409.740460 -67.061702
[52,] 742.429610 -409.740460
[53,] 2.641703 742.429610
[54,] 426.608958 2.641703
[55,] -282.259022 426.608958
[56,] 157.207432 -282.259022
[57,] -507.242858 157.207432
[58,] -399.402334 -507.242858
[59,] 840.017814 -399.402334
[60,] -274.249669 840.017814
[61,] 748.485751 -274.249669
[62,] -292.742224 748.485751
[63,] 187.531841 -292.742224
[64,] -14.368422 187.531841
[65,] -582.587730 -14.368422
[66,] 203.988998 -582.587730
[67,] 525.863850 203.988998
[68,] 306.061768 525.863850
[69,] -1222.664697 306.061768
[70,] -261.754914 -1222.664697
[71,] 744.005326 -261.754914
[72,] 506.761771 744.005326
[73,] 634.488982 506.761771
[74,] 625.318778 634.488982
[75,] 439.826349 625.318778
[76,] 124.031823 439.826349
[77,] 2.803184 124.031823
[78,] -997.529148 2.803184
[79,] 468.546704 -997.529148
[80,] 901.254325 468.546704
[81,] -1337.622467 901.254325
[82,] -1141.718150 -1337.622467
[83,] 243.809405 -1141.718150
[84,] -1107.167828 243.809405
[85,] -455.525434 -1107.167828
[86,] -57.309364 -455.525434
[87,] -1273.924613 -57.309364
[88,] -91.226273 -1273.924613
[89,] 877.043742 -91.226273
[90,] 643.672828 877.043742
[91,] 526.768288 643.672828
[92,] 1635.528144 526.768288
[93,] -254.121475 1635.528144
[94,] -479.645277 -254.121475
[95,] 594.572746 -479.645277
[96,] -1019.952397 594.572746
[97,] 12.356647 -1019.952397
[98,] 136.043064 12.356647
[99,] 254.570150 136.043064
[100,] 287.918080 254.570150
[101,] 348.203253 287.918080
[102,] -588.447605 348.203253
[103,] 2144.464320 -588.447605
[104,] 636.383994 2144.464320
[105,] 92.952908 636.383994
[106,] -465.658149 92.952908
[107,] 848.048582 -465.658149
[108,] 572.590212 848.048582
[109,] 633.510364 572.590212
[110,] -261.544254 633.510364
[111,] -665.093760 -261.544254
[112,] 774.883468 -665.093760
[113,] 19.182073 774.883468
[114,] -652.247073 19.182073
[115,] 439.135276 -652.247073
[116,] 460.144998 439.135276
[117,] -192.224423 460.144998
[118,] -1512.018502 -192.224423
[119,] 594.132144 -1512.018502
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -126.930269 -96.072801
2 -49.127419 -126.930269
3 278.169159 -49.127419
4 160.118461 278.169159
5 170.841800 160.118461
6 1388.919184 170.841800
7 383.724031 1388.919184
8 1366.203253 383.724031
9 -803.751973 1366.203253
10 -1064.457643 -803.751973
11 232.736433 -1064.457643
12 -644.073134 232.736433
13 66.636923 -644.073134
14 118.144036 66.636923
15 -232.372313 118.144036
16 -104.545470 -232.372313
17 1014.739573 -104.545470
18 -1200.844853 1014.739573
19 139.426858 -1200.844853
20 1197.555914 139.426858
21 -1590.774925 1197.555914
22 -640.740223 -1590.774925
23 866.258345 -640.740223
24 -736.048084 866.258345
25 -1231.082832 -736.048084
26 -471.239545 -1231.082832
27 -506.830764 -471.239545
28 161.334919 -506.830764
29 232.939566 161.334919
30 -941.895696 232.939566
31 569.954537 -941.895696
32 204.376532 569.954537
33 -509.084271 204.376532
34 -1115.944426 -509.084271
35 106.368854 -1115.944426
36 -46.037184 106.368854
37 902.318550 -46.037184
38 -951.820481 902.318550
39 -387.211960 -951.820481
40 436.471249 -387.211960
41 -634.344968 436.471249
42 -1165.515323 -634.344968
43 325.374345 -1165.515323
44 246.690498 325.374345
45 417.516179 246.690498
46 -937.268084 417.516179
47 368.643847 -937.268084
48 -187.816909 368.643847
49 523.629077 -187.816909
50 -67.061702 523.629077
51 -409.740460 -67.061702
52 742.429610 -409.740460
53 2.641703 742.429610
54 426.608958 2.641703
55 -282.259022 426.608958
56 157.207432 -282.259022
57 -507.242858 157.207432
58 -399.402334 -507.242858
59 840.017814 -399.402334
60 -274.249669 840.017814
61 748.485751 -274.249669
62 -292.742224 748.485751
63 187.531841 -292.742224
64 -14.368422 187.531841
65 -582.587730 -14.368422
66 203.988998 -582.587730
67 525.863850 203.988998
68 306.061768 525.863850
69 -1222.664697 306.061768
70 -261.754914 -1222.664697
71 744.005326 -261.754914
72 506.761771 744.005326
73 634.488982 506.761771
74 625.318778 634.488982
75 439.826349 625.318778
76 124.031823 439.826349
77 2.803184 124.031823
78 -997.529148 2.803184
79 468.546704 -997.529148
80 901.254325 468.546704
81 -1337.622467 901.254325
82 -1141.718150 -1337.622467
83 243.809405 -1141.718150
84 -1107.167828 243.809405
85 -455.525434 -1107.167828
86 -57.309364 -455.525434
87 -1273.924613 -57.309364
88 -91.226273 -1273.924613
89 877.043742 -91.226273
90 643.672828 877.043742
91 526.768288 643.672828
92 1635.528144 526.768288
93 -254.121475 1635.528144
94 -479.645277 -254.121475
95 594.572746 -479.645277
96 -1019.952397 594.572746
97 12.356647 -1019.952397
98 136.043064 12.356647
99 254.570150 136.043064
100 287.918080 254.570150
101 348.203253 287.918080
102 -588.447605 348.203253
103 2144.464320 -588.447605
104 636.383994 2144.464320
105 92.952908 636.383994
106 -465.658149 92.952908
107 848.048582 -465.658149
108 572.590212 848.048582
109 633.510364 572.590212
110 -261.544254 633.510364
111 -665.093760 -261.544254
112 774.883468 -665.093760
113 19.182073 774.883468
114 -652.247073 19.182073
115 439.135276 -652.247073
116 460.144998 439.135276
117 -192.224423 460.144998
118 -1512.018502 -192.224423
119 594.132144 -1512.018502
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7ss1l1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ss1l1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9l1ip1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10l1ip1292285786.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11o1gu1292285786.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12rkf01292285786.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13nud91292285786.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/149ubf1292285786.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15uva31292285786.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16gd891292285786.tab")
+ }
>
> try(system("convert tmp/1eild1292285786.ps tmp/1eild1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/26r2g1292285786.ps tmp/26r2g1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/36r2g1292285786.ps tmp/36r2g1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/46r2g1292285786.ps tmp/46r2g1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/5hiji1292285786.ps tmp/5hiji1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hiji1292285786.ps tmp/6hiji1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ss1l1292285786.ps tmp/7ss1l1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ss1l1292285786.ps tmp/8ss1l1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/9l1ip1292285786.ps tmp/9l1ip1292285786.png",intern=TRUE))
character(0)
> try(system("convert tmp/10l1ip1292285786.ps tmp/10l1ip1292285786.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.383 1.720 7.671